Technostress in the age of digital transformation and AI: A bibliometric–systematic literature review for HRM research

Digital transformation and artificial intelligence are reshaping human resource management through algorithmic recruitment, automated evaluation, predictive analytics, and generative tools. While these systems improve efficiency, they also intensify technostress through opacity, surveillance, reduced control, and digitally intensified work arrangements. Responding to a fragmented literature spanning both AI-enabled and broader digital work systems, this study provides a B-SLR that maps technostress in digital transformation while identifying AI-specific stressors as a key emerging stream for HRM research. Drawing on 194 Scopus-indexed articles, we combine performance analysis and science mapping to identify publication trends, dominant themes, and intellectual structures. The review shows how AI-specific stressors extend established technostress mechanisms and shift attention toward transparency, control, fairness, and responsible HRM design. We conclude with actionable implications for researchers and practitioners aiming to design more transparent, responsible, and sustainable digital and AI-enabled HRM systems.